Abstract

This paper describes the function of a software tool for identifying urban agglomerations in low-information settings using free, open data. The framework outlined here is designed to work using polygon data. This paper describes the advantages and disadvantages of using polygon-based geographies in regional analysis, discusses the practical and ethical challenges of distinguishing urban from rural regions, and discusses the relevance of this tool in the analysis of global city regions. It also describes the logical structure of our polygon-based software tool and directs interested readers to the source code. We finally examine the agglomeration results for Sri Lanka and compare them with published urbanization figures. We conclude that there are very large disparities between our model’s outputs and the urbanization estimates from the United Nations and that our tools can be used as a less discretionary way to identify actual levels of urbanization. We hope that other analysts will continue to refine the progression toward a less discretionary model of identifying urban regions.

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